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arXiv · 1808.07243

Controversy Rules - Discovering Regions Where Classifiers (Dis-)Agree Exceptionally

Oren Zeev-Ben-Mordehai·Wouter Duivesteijn·Mykola Pechenizkiy
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Abstract

Finding regions for which there is higher controversy among different classifiers is insightful with regards to the domain and our models. Such evaluation can falsify assumptions, assert some, or also, bring to the attention unknown phenomena. The present work describes an algorithm, which is based on the Exceptional Model Mining framework, and enables that kind of investigations. We explore several public datasets and show the usefulness of this approach in classification tasks. We show in this paper a few interesting observations about those well explored datasets, some of which are general knowledge, and other that as far as we know, were not reported before.

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Oren Zeev-Ben-Mordehai, Wouter Duivesteijn, Mykola Pechenizkiy. 2018-08-22. Controversy Rules - Discovering Regions Where Classifiers (Dis-)Agree Exceptionally. https://arxiv.org/abs/1808.07243

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